Model Context Protocol
MCP is a standard for connecting models to external capabilities. For a harness, it is the contract that turns ad-hoc tool prompting into a structured, portable, and auditable action layer.
MCP defines a common interface between clients (IDEs, terminals, apps, harness runtimes) and servers that expose tools, resources, and prompts. Instead of every harness inventing custom request formats, MCP lets them speak one consistent protocol. That consistency is what enables reusable integrations across ecosystems.
An agent harness succeeds or fails based on how safely and reliably it can act. MCP improves this by making tool contracts explicit, schema-driven, and machine-readable. Planning gets better because the model can inspect capability metadata. Execution gets safer because calls are validated against declared input shapes. Review gets easier because each call and response is captured as a first-class protocol event.
- Tools: callable actions such as search, file edits, shell commands, or API operations.
- Resources: structured context the model can read (documents, state snapshots, configuration).
- Prompts: reusable prompt templates that standardize recurring workflows.
- Schemas: typed parameter/result contracts that reduce ambiguity and runtime errors.
- Interoperability: one tool server can be consumed by multiple clients and models.
- Portability: swap model vendors without rebuilding your integration layer.
- Governance: centralize permissions, logging, and policy checks around tool access.
- Velocity: add capabilities quickly by plugging in servers instead of writing one-off glue.
During orient, the harness loads available MCP servers and tool manifests. During decide, the model chooses a tool call based on declared capabilities and constraints. During act, the client sends a validated invocation to the server. During reflect, the harness parses structured results, updates state, and decides whether to continue, recover, or stop. This keeps the loop legible and reduces hidden prompt behavior.
Good MCP integration is not just wiring transport. Keep servers narrowly scoped by domain, require explicit permission boundaries, enforce timeouts and retry policies, and treat tool output as untrusted input that still needs validation. Add observability around call latency, failure modes, and retry decisions so your harness can adapt and operators can audit behavior.
Most reliability issues come from over-broad tool permissions, weak schema definitions, and missing result validation. Another common issue is treating MCP as autonomy by itself; it is only the interface. The harness still needs planning quality, stop conditions, safety policies, and evaluation criteria to produce dependable outcomes.